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fix(spark): support consistent hashing clustering on non-partitioned tables #18968

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fix(spark): support consistent hashing clustering on non-partitioned tables #18968

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e4a1779
fix(spark): support consistent hashing clustering on non-partitioned …
ad1happy2go Jun 10, 2026
ce8febd
test(spark): merge non-partitioned resizing into testResizing per review
ad1happy2go Jun 12, 2026
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6 changes: 4 additions & 2 deletions ...hudi/client/clustering/run/strategy/SingleSparkJobConsistentHashingExecutionStrategy.java
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Original file line number Diff line number Diff line change
Expand Up @@ -111,7 +111,8 @@ private List<WriteStatus> performBucketMergeForGroup(ReaderContextFactory<T> rea
Option<Map<String, String>> extraMetadata = clusteringGroup.getExtraMetadata();
ValidationUtils.checkArgument(extraMetadata.isPresent(), "Extra metadata should be present for consistent hashing operations");
String partition = extraMetadata.get().get(BaseConsistentHashingBucketClusteringPlanStrategy.METADATA_PARTITION_KEY);
ValidationUtils.checkArgument(!StringUtils.isNullOrEmpty(partition), "Partition should not be null or empty");
// Note: partition can be an empty string for non-partitioned tables, so only check for null here.
ValidationUtils.checkArgument(partition != null, "Partition should not be null");
List<ConsistentHashingNode> nodes = decodeConsistentHashingNodes(clusteringGroup);
Option<ConsistentHashingNode> newBucket = Option.fromJavaOptional(nodes.stream().filter(node -> node.getTag() == ConsistentHashingNode.NodeTag.REPLACE).findFirst());
ValidationUtils.checkArgument(newBucket.isPresent(), "New bucket should be present for merge operation");
Expand Down Expand Up @@ -197,7 +198,8 @@ private List<WriteStatus> performBucketSplitForGroup(ReaderContextFactory<T> rea
Option<Map<String, String>> extraMetadata = clusteringGroup.getExtraMetadata();
ValidationUtils.checkArgument(extraMetadata.isPresent(), "Extra metadata should be present for consistent hashing operations");
String partition = extraMetadata.get().get(BaseConsistentHashingBucketClusteringPlanStrategy.METADATA_PARTITION_KEY);
ValidationUtils.checkArgument(!StringUtils.isNullOrEmpty(partition), "Partition should not be null or empty");
// Note: partition can be an empty string for non-partitioned tables, so only check for null here.
ValidationUtils.checkArgument(partition != null, "Partition should not be null");
List<ConsistentHashingNode> nodes = decodeConsistentHashingNodes(clusteringGroup);
Integer seqNo = Integer.parseInt(extraMetadata.get().get(BaseConsistentHashingBucketClusteringPlanStrategy.METADATA_SEQUENCE_NUMBER_KEY));
HoodieConsistentHashingMetadata metadata = new HoodieConsistentHashingMetadata((short) 0, partition, instantTime, 0, seqNo + 1, Collections.emptyList());
Expand Down
36 changes: 32 additions & 4 deletions ...i-spark/src/test/java/org/apache/hudi/functional/TestSparkConsistentBucketClustering.java
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Expand Up @@ -34,6 +34,7 @@
import org.apache.hudi.common.schema.HoodieSchema;
import org.apache.hudi.common.schema.HoodieSchemaField;
import org.apache.hudi.common.schema.HoodieSchemaType;
import org.apache.hudi.common.table.HoodieTableConfig;
import org.apache.hudi.common.table.HoodieTableMetaClient;
import org.apache.hudi.common.testutils.HoodieTestDataGenerator;
import org.apache.hudi.common.testutils.HoodieTestUtils;
Expand All @@ -49,6 +50,7 @@
import org.apache.hudi.index.HoodieIndex;
import org.apache.hudi.index.bucket.ConsistentBucketIndexUtils;
import org.apache.hudi.keygen.constant.KeyGeneratorOptions;
import org.apache.hudi.keygen.constant.KeyGeneratorType;
import org.apache.hudi.storage.StoragePath;
import org.apache.hudi.table.HoodieSparkTable;
import org.apache.hudi.table.HoodieTable;
Expand Down Expand Up @@ -102,13 +104,24 @@ public void setup(int maxFileSize, Map<String, String> options) throws IOExcepti
}

public void setup(int maxFileSize, Map<String, String> options, boolean singleJob) throws IOException {
setup(maxFileSize, options, singleJob, false);
}

public void setup(int maxFileSize, Map<String, String> options, boolean singleJob, boolean nonPartitioned) throws IOException {
initPath();
initSparkContexts();
initTestDataGenerator();
initHoodieStorage();
Properties props = getPropertiesForKeyGen(true);
props.putAll(options);
props.setProperty(KeyGeneratorOptions.RECORDKEY_FIELD_NAME.key(), "_row_key");
if (nonPartitioned) {
// Non-partitioned tables produce records with an empty partition path and use the non-partition key generator.
dataGen = new HoodieTestDataGenerator(new String[] {HoodieTestDataGenerator.NO_PARTITION_PATH});
props.setProperty(HoodieWriteConfig.KEYGENERATOR_TYPE.key(), KeyGeneratorType.NON_PARTITION.name());
props.setProperty(KeyGeneratorOptions.PARTITIONPATH_FIELD_NAME.key(), "");
props.remove(HoodieTableConfig.PARTITION_FIELDS.key());
}
metaClient = HoodieTestUtils.init(storageConf, basePath, HoodieTableType.MERGE_ON_READ, props);
config = getConfigBuilder().withProps(props)
.withIndexConfig(HoodieIndexConfig.newBuilder().fromProperties(props)
Expand All @@ -130,16 +143,21 @@ public void tearDown() throws IOException {
}

/**
* Test resizing with bucket number upper bound and lower bound
* Test resizing with bucket number upper bound and lower bound, on both partitioned and non-partitioned tables.
*
* <p>Non-partitioned coverage guards GitHub issue #18161: consistent hashing clustering used to fail on
* non-partitioned tables because the empty partition path was rejected by the execution strategy. For a
* non-partitioned table {@code dataGen.getPartitionPaths()} returns the single empty partition path, so the
* assertions below cover both cases without branching.
*
* @throws IOException
*/
@ParameterizedTest
@MethodSource("configParams")
public void testResizing(boolean isSplit, boolean rowWriterEnable, boolean single) throws IOException {
@MethodSource("resizingConfigParams")
public void testResizing(boolean isSplit, boolean rowWriterEnable, boolean single, boolean nonPartitioned) throws IOException {
final int maxFileSize = isSplit ? 5120 : 128 * 1024 * 1024;
final int targetBucketNum = isSplit ? 14 : 4;
setup(maxFileSize, Collections.emptyMap(), single);
setup(maxFileSize, Collections.emptyMap(), single, nonPartitioned);
config.setValue("hoodie.datasource.write.row.writer.enable", String.valueOf(rowWriterEnable));
config.setValue("hoodie.metadata.enable", "false");
writeData(2000, true);
Expand Down Expand Up @@ -384,6 +402,16 @@ private static Stream<Arguments> configParams() {
);
}

// configParams crossed with the partitioned / non-partitioned dimension (isSplit, rowWriterEnable, single, nonPartitioned).
private static Stream<Arguments> resizingConfigParams() {
return configParams().flatMap(args -> {
Object[] a = args.get();

@hudi-agent hudi-agent Jun 13, 2026

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🤖 nit: could you rename a to something like origArgs or baseArgs? The single-letter name is a bit hard to follow when it's indexed three times on the lines below.

- AI-generated; verify before applying. React 👍/👎 to flag quality.

return Stream.of(
Arguments.of(a[0], a[1], a[2], false),
Arguments.of(a[0], a[1], a[2], true));
});
}

private static Stream<Arguments> configParamsForSorting() {
return Stream.of(
Arguments.of("begin_lat", true),
Expand Down
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